Thanks Chuck.
I am trying to use Successive Over-relaxation to so=
lve
linear equations defined by M*v=3Dq.
There are several goals:
1. Eventually (in production) I need it to be=
fast.
2. I am playing with the guts of the algorithm for=
now, to
see how it works. that means i need some control for now.
3. Even in production, there is a chance i'd like t=
o have
the ability to tinker with the algorithm.
On 2/15/07, Geoff=
rey
Zhu <gzhu@peak6.com> wrote:<=
/SPAN>
Hi,
I
am new to numpy. I'd like to know if it is possible to code
efficient
iterative procedures with numpy.
Specifically, I have=
the
following problem.
M is an N*N matrix. Q is a N*1 vector. V is an N=
*1
vector I am trying to
find iteratively from the initial value V_0. The=
procedure is simply
to
calculate
V_{n+1}[i]=3D3D1/M[I,i]*(q[i]-
(M[i,1]*v_{n+1}[1=
]+M[I,2]*v_{n+1}[2]+..+M[i,i-1]*v_{n+1}[i-1])
-
(M[I,i+1]*v_{n}[i+1]+M[I,i+2]*v_{n}[i+2]+..+M[I,N]*v_{n}[N]))
I
do not see that this is something that can esaily be vectorized,
is
it?
I think it would be better if you stated what the actual problem is=
. Is
it a differential equation, for instance. That way we can determine what the=
problem class is and what algorithms are available to solve it.
Chuck
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